Method for evaluating service life of lithium iron phosphate lithium ion battery and related device
By dividing and calculating the voltage range of charging data for lithium iron phosphate lithium-ion batteries, and combining this with lifetime correction coefficients for optimized prediction, the problem of inaccurate lifetime prediction in existing technologies has been solved, achieving more accurate lifetime assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-02
- Publication Date
- 2026-04-28
AI Technical Summary
The existing technology has a low accuracy rate in predicting the lifespan of military-grade lithium iron phosphate batteries, which affects the assessment of the health and operational status of military power batteries.
By acquiring effective charging data, the charging data is divided into different voltage ranges, and the charging capacity and capacity increment data are calculated. The lifespan prediction data is calculated using the lifespan correction coefficient and preset weights. The accuracy is improved by verifying and optimizing the prediction results.
This improves the accuracy and reliability of lithium iron phosphate (LFP) lithium-ion battery life prediction, ensuring more accurate health status assessment of military power batteries.
Smart Images
Figure CN121933965A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of battery management, and in particular to a method and related apparatus for assessing the lifespan of lithium iron phosphate batteries. Background Technology
[0002] Military batteries can be classified into irreversible batteries and reversible batteries according to their working principle. Irreversible batteries, generally called primary batteries, generate current through oxidation-reduction reactions between electrodes, converting chemical energy into electrical energy. Because the internal oxidation-reduction reactions are irreversible, they generally only function once after activation, hence they are also called primary batteries. Their main applications include serving as backup batteries to provide power in destructive weapons; typical examples include thermal batteries, silver-zinc batteries, and lithium / thionyl chloride batteries. Reversible batteries refer to batteries where the oxidation-reduction reactions between electrodes are reversible: during discharge, oxidation occurs at the negative electrode and reduction occurs at the positive electrode; during charging, reduction occurs at the negative electrode and oxidation occurs at the positive electrode. Reversible batteries can not only convert chemical energy into electrical energy but also convert externally input electrical energy into chemical energy for storage within the battery. Therefore, reversible batteries can be used multiple times and are generally called secondary batteries. They are typically used as rechargeable energy storage devices, used in the start-stop and power batteries of military equipment or vehicles; typical examples include lead-acid batteries and lithium-ion batteries.
[0003] As military vehicles increasingly demand higher range and power, lithium-ion batteries, due to their small size, light weight, and high energy density, are gradually being used as power batteries in military vehicles. Among them, lithium iron phosphate batteries (a type of lithium-ion battery) are particularly suitable as power batteries for military vehicles due to their higher safety.
[0004] As a military power battery, its current state of life and remaining service life are related to the healthy operation of the vehicle battery. Therefore, the accuracy of its current life is crucial. Existing solutions have a low accuracy rate in predicting the life of military power batteries (lithium iron phosphate batteries). Summary of the Invention
[0005] To address the shortcomings of existing technologies, this invention provides a method for assessing the lifespan of lithium iron phosphate batteries, thereby solving the problem of low accuracy in predicting the lifespan of military power batteries (lithium iron phosphate batteries) in existing technologies.
[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution.
[0007] In a first aspect, this application provides a method for evaluating the lifespan of lithium iron phosphate batteries, comprising the following steps:
[0008] Obtain valid charging data of the lithium iron phosphate battery under test. The charging data is the charging data of the lithium iron phosphate battery under test during the charging process when the remaining capacity is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. According to the preset voltage range set, the effective charging data is divided into first stage charging data corresponding to the first preset voltage range in the preset voltage range set, second stage charging data corresponding to the second preset voltage range in the preset voltage range set, and third stage charging data corresponding to the third preset voltage range in the preset voltage range set. Based on the charging start time, charging end time and battery current in the first stage charging data, the charging capacity within the first preset voltage range is calculated, and the current lifespan of the battery is calculated based on the charging capacity, the remaining charging capacity at the start of the first stage charging data, the remaining charging capacity at the end of the first stage charging data and the capacity value of the lithium iron phosphate battery under full charge. Based on the battery capacity change data and battery voltage change data in the second stage charging data, the capacity increment data of the lithium iron phosphate battery under test is calculated, and the offset data is determined based on the capacity increment data and the factory data of the lithium iron phosphate battery under test. The life correction coefficient is calculated based on the offset data, the factory data and the termination data of the lithium iron phosphate battery under test at the end of its life. The life prediction data of the lithium iron phosphate battery under test is calculated based on the current life status of the battery, the life correction coefficient and the preset weight. Based on the third-stage charging data, the lifespan verification value of the lithium iron phosphate battery under test is calculated, and the lifespan prediction data is verified using the lifespan verification value. If the verification passes, the lifespan prediction data is used as output data; if the verification fails, the preset weights are modified, and the lifespan re-prediction data of the lithium iron phosphate battery under test is calculated based on the modified preset weights until the lifespan re-prediction data is verified by the lifespan verification value, and the lifespan re-prediction data is used as output data.
[0009] Optionally, the step of obtaining valid charging data of the lithium iron phosphate battery under test includes: Acquire charging data of the lithium iron phosphate lithium-ion battery under test during the charging process when the remaining charge is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. The charging data is processed to remove invalid data, so as to obtain the valid charging data of the lithium iron phosphate battery to be tested. The invalid data includes data where the battery state is zero, the lowest and highest single cell voltages are both zero, the battery state is empty, and the lowest and highest single cell voltages are both empty.
[0010] Optionally, the step of determining the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test includes: With voltage as the x-axis and capacity increment data as the y-axis, a current voltage-capacity increment data curve is plotted based on the capacity increment data, and the x-axis value corresponding to the characteristic peak in the current voltage-capacity increment data curve is identified and recorded as the current characteristic peak voltage. With voltage as the horizontal axis and capacity increment data as the vertical axis, a factory voltage-capacity increment data curve is plotted based on the factory data of the lithium iron phosphate lithium-ion battery to be tested, and the horizontal axis value corresponding to the characteristic peak in the factory voltage-capacity increment data curve is identified and recorded as the factory characteristic peak voltage. The offset data is determined based on the current characteristic peak voltage and the factory characteristic peak voltage.
[0011] Optionally, the step of calculating the life correction factor based on the offset data, the factory data, and the termination data of the lithium iron phosphate battery under test at the end of its life includes: With voltage as the horizontal axis and capacity increment data as the vertical axis, a termination voltage-capacity increment data curve is plotted based on the termination data of the lithium iron phosphate battery under test at the end of its life. The horizontal axis value corresponding to the characteristic peak in the termination voltage-capacity increment data curve is identified and recorded as the termination characteristic peak voltage. The lifetime correction factor is calculated based on the offset data, the factory characteristic peak voltage, and the termination characteristic peak voltage.
[0012] Optionally, the step of calculating the lifetime verification value of the lithium iron phosphate battery under test based on the third-stage charging data includes: Based on the charging start time, charging end time, and battery current in the third stage charging data, the charging capacity within the third preset voltage range is calculated. Based on the charging capacity within the third preset voltage range, the remaining charging capacity at the start of the third stage charging data, the remaining charging capacity at the end of the third stage charging data, and the capacity value of the lithium iron phosphate battery under test at full charge, the life verification value of the lithium iron phosphate battery under test is calculated.
[0013] Optionally, the step of verifying the lifetime prediction data using the lifetime verification value, and using the lifetime prediction data as output data if the verification passes, includes: Calculate the difference between the lifetime verification value and the lifetime prediction data. If the difference is less than or equal to a threshold, the lifetime prediction data is verified and the lifetime prediction data is used as output data.
[0014] Optionally, the step of calculating the life prediction data of the lithium iron phosphate battery under test based on the current life state of the battery, the life correction coefficient, and the preset weight includes: Based on the current battery lifespan status, the lifespan correction coefficient, and the preset weight, the formula is used: (6) Calculate the predicted lifetime data of the lithium iron phosphate battery under test, where SOH( α , β (This refers to lifespan prediction data.) m The weights are the initial capacity calculation values for battery life in the preset weights. α This indicates the current state of battery life. n The weights are calculated based on the battery life correction coefficient in the preset weights. β This is the lifetime correction factor.
[0015] Secondly, this application provides a lithium iron phosphate lithium-ion battery life assessment device, the device comprising: The data extraction module is used to obtain the effective charging data of the lithium iron phosphate battery under test. The charging data is the charging data of the lithium iron phosphate battery under test during the charging process when the remaining power is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. The segmentation module is used to divide the effective charging data into a first stage charging data corresponding to a first preset voltage interval within the preset voltage interval set, a second stage charging data corresponding to a second preset voltage interval within the preset voltage interval set, and a third stage charging data corresponding to a third preset voltage interval within the preset voltage interval set, according to a preset voltage interval set. The first calculation module is used to calculate the charging capacity within the first preset voltage range based on the charging start time, charging end time and battery current in the first stage charging data, and to calculate the current lifespan status of the battery based on the charging capacity, the remaining charging capacity at the start of the first stage charging data, the remaining charging capacity at the end of the first stage charging data and the capacity value of the lithium iron phosphate battery under full charge. The second calculation module is used to calculate the capacity increment data of the lithium iron phosphate battery under test based on the battery capacity change data and battery voltage change data in the second stage charging data, and to determine the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test. It also calculates the life correction coefficient based on the offset data, the factory data and the termination data of the lithium iron phosphate battery under test at the end of its life, and calculates the life prediction data of the lithium iron phosphate battery under test based on the current life status of the battery, the life correction coefficient and the preset weight. The verification module is used to calculate the life verification value of the lithium iron phosphate battery under test based on the third-stage charging data, and to verify the life prediction data using the life verification value. If the verification passes, the life prediction data is used as output data; if the verification fails, the preset weight is modified, and the life re-prediction data of the lithium iron phosphate battery under test is calculated based on the modified preset weight, until the life re-prediction data is verified by the life verification value, and the life re-prediction data is used as output data.
[0016] Thirdly, this application also provides an electronic device, including a memory, a processor, and a first computer program stored in the memory and executable on the processor, wherein the processor executes the first computer program to implement the lithium iron phosphate lithium-ion battery life assessment method as described above.
[0017] Fourthly, this application also provides a computer-readable storage medium storing a second computer program, which, when executed by a processor, implements the lithium iron phosphate lithium-ion battery life assessment method as described above.
[0018] Beneficial effects: This application improves the accuracy of calculation results by dividing the effective charging data into a preset voltage range set and using data within different ranges to predict, correct, and verify the calculated lifetime value. The calculated result value can be verified and optimized in reverse. Attached Figure Description
[0019] Figure 1 This is a flowchart illustrating the operation of a lithium iron phosphate lithium-ion battery life assessment method according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a lithium iron phosphate lithium-ion battery life assessment system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a computer-readable storage medium provided in an embodiment of this application. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
[0021] The embodiments described in this application are merely some, not all, embodiments of the present invention. Based on the spirit of the present invention, all other embodiments obtained by those skilled in the art without inventive effort are within the protection scope of the present invention.
[0022] See Figure 1 As shown, the present invention provides a method for evaluating the lifespan of lithium iron phosphate batteries, comprising the following steps: S110. Obtain valid charging data of the lithium iron phosphate battery to be tested. The charging data is the charging data of the lithium iron phosphate battery to be tested during the charging process when the remaining power is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. In one possible implementation, the step of acquiring the effective charging data of the lithium iron phosphate battery under test includes: Acquire charging data of the lithium iron phosphate lithium-ion battery under test during the charging process when the remaining charge is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. The charging data is processed to remove invalid data, so as to obtain the valid charging data of the lithium iron phosphate battery to be tested. The invalid data includes data where the battery state is zero, the lowest and highest single cell voltages are both zero, the battery state is empty, and the lowest and highest single cell voltages are both empty.
[0023] For example, the main fields for extracting all data during the battery charging phase include device identification code, time, battery state, remaining capacity (SOC), current, highest single-cell voltage (Vmax), and lowest single-cell voltage (Vmin). Invalid data removal: remove 0 values (state=0 or both lowest and highest single-cell voltages are 0), and remove null values (state is empty or both lowest and highest single-cell voltages are empty). Select charging processes and data where the initial SOC is less than 5% and the final SOC is greater than or equal to 98%.
[0024] S120. According to the preset voltage range set, the effective charging data is divided into first stage charging data corresponding to the first preset voltage range in the preset voltage range set, second stage charging data corresponding to the second preset voltage range in the preset voltage range set, and third stage charging data corresponding to the third preset voltage range in the preset voltage range set. For example, the first preset voltage range in the preset voltage range set is 2.5~3.34V, the second preset voltage range in the preset voltage range set is 3.351~3.375V, and the third preset voltage range in the preset voltage range set is 3.4~3.65V.
[0025] S130. Based on the charging start time, charging end time and battery current in the first stage charging data, calculate the charging capacity in the first preset voltage range, and calculate the current lifespan state of the battery based on the charging capacity, the remaining charging capacity at the start of the first stage charging data, the remaining charging capacity at the end of the first stage charging data and the capacity value of the lithium iron phosphate battery under full charge. For example, the charging capacity within the first preset voltage range is calculated using the following formula:
[0026] Where: deltaQ1: the amount of charge added to the battery between times t1 and t2, Ah; t1: the start time of charging of the battery within the first judgment interval; t2: the end time of charging of the battery within the first judgment interval, i.e., the time when the voltage reaches 3.34V; I is the battery current.
[0027] Based on the charged capacity, the remaining capacity at the start of charging in the first stage of charging data, the remaining capacity at the end of charging in the first stage of charging data, and the capacity value of the lithium iron phosphate battery under full charge, the current lifespan state α of the battery is calculated using the following formula:
[0028] In the formula: α : Battery life status in its current state (current battery life status, soh), % deltaQ The amount of electricity charged into the battery between times t1 and t2, in Ah; soc 1: The state of charge (SOC) of the battery at the start time t1 of the first judgment interval, % soc 2: The state of charge (SOC) of the battery at time t2, the end of charging within the first judgment interval, i.e., the SOC when the voltage reaches 3.34V, % Q 0: Battery capacity at full charge in its initial state, in Ah; In one possible implementation, the step of determining the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test includes: With voltage as the x-axis and capacity increment data as the y-axis, a current voltage-capacity increment data curve is plotted based on the capacity increment data, and the x-axis value corresponding to the characteristic peak in the current voltage-capacity increment data curve is identified and recorded as the current characteristic peak voltage. With voltage as the horizontal axis and capacity increment data as the vertical axis, a factory voltage-capacity increment data curve is plotted based on the factory data of the lithium iron phosphate lithium-ion battery to be tested, and the horizontal axis value corresponding to the characteristic peak in the factory voltage-capacity increment data curve is identified and recorded as the factory characteristic peak voltage. The offset data is determined based on the current characteristic peak voltage and the factory characteristic peak voltage.
[0029] For example, a "V-dQ / dV" curve is plotted with voltage on the x-axis, capacity increment data (Cinc) on the y-axis, and individual cell voltage on the x-axis. The x-axis value Vqv corresponding to the characteristic peak in the curve is then identified. The calculated x-axis value Vqv corresponding to the characteristic peak is compared with the initial Vqv0.
[0030] For example, the capacity increment Cinc of the second preset voltage range is calculated using the following formula:
[0031] Where Cinc: battery capacity increment, Ah / V; dQ: battery capacity change, Ah; dV: battery voltage change, V.
[0032] The offset of the characteristic peak relative to the initial state is calculated using the following formula:
[0033] In the formula: deltaV Battery characteristic peak shift, V; V qv0 : Characteristic peak position (factory characteristic peak voltage) in the initial state of the battery, V; V qv : The position of the characteristic peak (current characteristic peak voltage) in the current state of the battery, in V.
[0034] S140. Calculate the capacity increment data of the lithium iron phosphate battery under test based on the battery capacity change data and battery voltage change data in the second stage charging data, and determine the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test. Calculate the life correction coefficient based on the offset data, the factory data, and the termination data of the lithium iron phosphate battery under test at the end of its lifespan. Calculate the life prediction data of the lithium iron phosphate battery under test based on the current lifespan status of the battery, the life correction coefficient, and a preset weight. In one possible implementation, the step of calculating the life correction factor based on the offset data, the factory data, and the termination data of the lithium iron phosphate battery under test at the end of its life includes: With voltage as the horizontal axis and capacity increment data as the vertical axis, a termination voltage-capacity increment data curve is plotted based on the termination data of the lithium iron phosphate battery under test at the end of its life. The horizontal axis value corresponding to the characteristic peak in the termination voltage-capacity increment data curve is identified and recorded as the termination characteristic peak voltage. The lifetime correction factor is calculated based on the offset data, the factory characteristic peak voltage, and the termination characteristic peak voltage.
[0035] For example, based on the characteristic peak offset (the offset data), a correction coefficient is calculated using the following formula:
[0036] In the formula: β Current lifetime correction factor; V qvend : The location of the characteristic peak (termination characteristic peak voltage) at the end of battery life, in V; S150. Calculate the lifespan verification value of the lithium iron phosphate battery under test based on the third-stage charging data, and verify the lifespan prediction data using the lifespan verification value. If the verification passes, the lifespan prediction data is used as output data; if the verification fails, modify the preset weights, and calculate the lifespan re-prediction data of the lithium iron phosphate battery under test based on the modified preset weights, until the lifespan re-prediction data is verified by the lifespan verification value, and then use the lifespan re-prediction data as output data.
[0037] In one possible implementation, the step of calculating the lifetime verification value of the lithium iron phosphate battery under test based on the third-stage charging data includes: Based on the charging start time, charging end time, and battery current in the third stage charging data, the charging capacity within the third preset voltage range is calculated. Based on the charging capacity within the third preset voltage range, the remaining charging capacity at the start of the third stage charging data, the remaining charging capacity at the end of the third stage charging data, and the capacity value of the lithium iron phosphate battery under test at full charge, the life verification value of the lithium iron phosphate battery under test is calculated.
[0038] In one possible implementation, the step of verifying the lifetime prediction data using the lifetime verification value, and if the verification passes, using the lifetime prediction data as output data, includes: Calculate the difference between the lifetime verification value and the lifetime prediction data. If the difference is less than or equal to a threshold, the lifetime prediction data is verified and the lifetime prediction data is used as output data.
[0039] In one possible implementation, the step of calculating the life prediction data of the lithium iron phosphate battery under test based on the current life state of the battery, the life correction coefficient, and a preset weight includes: Based on the current battery lifespan status, the lifespan correction coefficient, and the preset weight, the formula is used: (6) Calculate the predicted lifetime data of the lithium iron phosphate battery under test, where SOH( α , β (This refers to lifespan prediction data.) m The weights are the initial capacity calculation values for battery life in the preset weights. α This indicates the current state of battery life. n The weights are calculated based on the battery life correction coefficient in the preset weights. β This is the lifetime correction factor.
[0040] For example, the integral deltaQ of battery current and time within the third stage charging data (3.4~3.65V, SOC range approximately [95-100%]) corresponding to the third preset voltage range is calculated using the following formula: (7) In the formula: deltaQ2: the amount of charge added to the battery between times t3 and t4, Ah; t3: the start time of charging the battery within the third judgment interval; t4: the end time of charging the battery within the third judgment interval, i.e., the time when the voltage reaches 3.65V.
[0041] The current battery life verification value γ is calculated based on the calculated charge amount deltaQ2, using the following formula: (8) In the formula: γ: Battery life verification value status (health status, SOH), % deltaQ2: The amount of charge the battery received between times t3 and t4, in Ah; soc3: The soc value of the battery at time t3, the start time of charging within the third judgment interval, in percentage terms. soc4: The soc value of the battery at time t4, the end of charging within the third judgment interval, i.e., the soc value when the voltage reaches 3.65V, % Q0: Battery capacity at full charge in its initial state, Ah; The difference between the estimated battery life SOH(α,β) and the verified battery life is calculated using the following formula: (9) In the formula: deltaSOH: The difference between the estimated battery life SOH(α,β) and the verified battery life, in percentages. SOH(α,β): Battery life state calculated based on the preliminary battery life calculation value and the correction factor, % γ: Battery life verification value status (health status, soh),%.
[0042] Compare the estimated battery SOH(α,β) with the battery life verification value γ. If the difference is within ±5%, output the current estimated SOH(α,β) as the final life estimate SOH(α,β,γ). Otherwise, adjust the ratio of m and n and recalculate the life value.
[0043] Secondly, such as Figure 2 As shown, this application provides a lithium iron phosphate lithium-ion battery life assessment device, the device comprising: The data extraction module 201 is used to obtain the effective charging data of the lithium iron phosphate lithium-ion battery under test. The charging data is the charging data of the lithium iron phosphate lithium-ion battery under test during the charging process when the remaining power is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. The partitioning module 202 is used to partition the effective charging data into a first stage charging data corresponding to a first preset voltage interval in the preset voltage interval set, a second stage charging data corresponding to a second preset voltage interval in the preset voltage interval set, and a third stage charging data corresponding to a third preset voltage interval in the preset voltage interval set, according to a preset voltage interval set. The first calculation module 203 is used to calculate the charging capacity within the first preset voltage range based on the charging start time, charging end time and battery current in the first stage charging data, and to calculate the current lifespan state of the battery based on the charging capacity, the remaining charging capacity at the start of the first stage charging data, the remaining charging capacity at the end of the first stage charging data and the capacity value of the lithium iron phosphate battery under full charge. The second calculation module 204 is used to calculate the capacity increment data of the lithium iron phosphate battery under test based on the battery capacity change data and battery voltage change data in the second stage charging data, and to determine the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test, to calculate the life correction coefficient based on the offset data, the factory data and the termination data of the lithium iron phosphate battery under test at the end of its life, and to calculate the life prediction data of the lithium iron phosphate battery under test based on the current life status of the battery, the life correction coefficient and the preset weight. The verification module 205 is used to calculate the life verification value of the lithium iron phosphate battery under test based on the third-stage charging data, and to verify the life prediction data using the life verification value. If the verification passes, the life prediction data is used as output data; if the verification fails, the preset weight is modified, and the life re-prediction data of the lithium iron phosphate battery under test is calculated based on the modified preset weight, until the life re-prediction data is verified by the life verification value, and the life re-prediction data is used as output data.
[0044] In one possible implementation, such as Figure 3 As shown, this application embodiment provides a terminal device 300, including: a memory 310, a processor 320, and a first computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the first computer program 311, it implements the steps of a lithium iron phosphate lithium-ion battery life assessment method.
[0045] In one possible implementation, such as Figure 4 As shown, this application embodiment provides a computer-readable storage medium 400, on which a second computer program 411 is stored. When the second computer program 411 is executed by a processor, it implements the steps of a lithium iron phosphate lithium-ion battery life assessment method.
[0046] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.
[0047] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0048] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.
[0049] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0050] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0051] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.
[0052] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0053] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
[0054] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.
Claims
1. A method for evaluating the lifespan of lithium iron phosphate lithium-ion batteries, characterized in that, Includes the following steps: Obtain valid charging data of the lithium iron phosphate battery under test. The charging data is the charging data of the lithium iron phosphate battery under test during the charging process when the remaining charge is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. According to the preset voltage range set, the effective charging data is divided into first-stage charging data corresponding to the first preset voltage range in the preset voltage range set, second-stage charging data corresponding to the second preset voltage range in the preset voltage range set, and third-stage charging data corresponding to the third preset voltage range in the preset voltage range set. Based on the charging start time, charging end time and battery current in the first stage charging data, the charging capacity within the first preset voltage range is calculated, and the current lifespan of the battery is calculated based on the charging capacity, the remaining charging capacity at the start of the first stage charging data, the remaining charging capacity at the end of the first stage charging data and the capacity value of the lithium iron phosphate battery under full charge. Based on the battery capacity change data and battery voltage change data in the second stage charging data, the capacity increment data of the lithium iron phosphate battery under test is calculated, and the offset data is determined based on the capacity increment data and the factory data of the lithium iron phosphate battery under test. The life correction coefficient is calculated based on the offset data, the factory data and the termination data of the lithium iron phosphate battery under test at the end of its life. The life prediction data of the lithium iron phosphate battery under test is calculated based on the current life status of the battery, the life correction coefficient and the preset weight. Based on the third-stage charging data, the lifespan verification value of the lithium iron phosphate battery under test is calculated, and the lifespan prediction data is verified using the lifespan verification value. If the verification passes, the lifespan prediction data is used as output data; if the verification fails, the preset weights are modified, and the lifespan re-prediction data of the lithium iron phosphate battery under test is calculated based on the modified preset weights until the lifespan re-prediction data is verified by the lifespan verification value, and the lifespan re-prediction data is used as output data.
2. The method for evaluating the lifespan of a lithium iron phosphate battery according to claim 1, characterized in that, The step of obtaining valid charging data of the lithium iron phosphate battery under test includes: Acquire charging data of the lithium iron phosphate lithium-ion battery under test during the charging process when the remaining charge is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. The charging data is processed to remove invalid data, so as to obtain the valid charging data of the lithium iron phosphate battery to be tested. The invalid data includes data where the battery state is zero, the lowest and highest single cell voltages are both zero, the battery state is empty, and the lowest and highest single cell voltages are both empty.
3. The method for evaluating the lifespan of a lithium iron phosphate battery according to claim 1, characterized in that, The step of determining the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test includes: With voltage as the horizontal axis and capacity increment data as the vertical axis, a current voltage-capacity increment data curve is plotted based on the capacity increment data, and the horizontal axis value corresponding to the characteristic peak in the current voltage-capacity increment data curve is identified and recorded as the current characteristic peak voltage. With voltage as the horizontal axis and capacity increment data as the vertical axis, a factory voltage-capacity increment data curve is plotted based on the factory data of the lithium iron phosphate lithium-ion battery to be tested, and the horizontal axis value corresponding to the characteristic peak in the factory voltage-capacity increment data curve is identified and recorded as the factory characteristic peak voltage. The offset data is determined based on the current characteristic peak voltage and the factory characteristic peak voltage.
4. The method for evaluating the lifespan of a lithium iron phosphate lithium-ion battery according to claim 3, characterized in that, The step of calculating the life correction factor based on the offset data, the factory data, and the termination data of the lithium iron phosphate battery under test at the end of its life includes: With voltage as the horizontal axis and capacity increment data as the vertical axis, a termination voltage-capacity increment data curve is plotted based on the termination data of the lithium iron phosphate battery under test at the end of its life. The horizontal axis value corresponding to the characteristic peak in the termination voltage-capacity increment data curve is identified and recorded as the termination characteristic peak voltage. The lifetime correction factor is calculated based on the offset data, the factory characteristic peak voltage, and the termination characteristic peak voltage.
5. The method for evaluating the lifespan of a lithium iron phosphate battery according to claim 1, characterized in that, The step of calculating the life verification value of the lithium iron phosphate battery under test based on the third-stage charging data includes: Based on the charging start time, charging end time, and battery current in the third stage charging data, the charging capacity within the third preset voltage range is calculated. Based on the charging capacity within the third preset voltage range, the remaining charging capacity at the start of the third stage charging data, the remaining charging capacity at the end of the third stage charging data, and the capacity value of the lithium iron phosphate battery under test at full charge, the life verification value of the lithium iron phosphate battery under test is calculated.
6. The method for evaluating the lifespan of a lithium iron phosphate battery according to claim 1, characterized in that, The step of verifying the lifetime prediction data using the lifetime verification value, and using the lifetime prediction data as output data if the verification passes, includes: Calculate the difference between the lifetime verification value and the lifetime prediction data. If the difference is less than or equal to a threshold, the lifetime prediction data is verified and the lifetime prediction data is used as output data.
7. The method for evaluating the lifespan of a lithium iron phosphate battery according to claim 1, characterized in that, The step of calculating the life prediction data of the lithium iron phosphate battery under test based on the current life status of the battery, the life correction coefficient, and the preset weight includes: Based on the current battery lifespan status, the lifespan correction coefficient, and the preset weight, the formula is used: (6) Calculate the predicted lifetime data of the lithium iron phosphate battery under test, where SOH( α , β (This refers to lifespan prediction data.) m The weights are the initial capacity calculation values for battery life in the preset weights. α This indicates the current state of battery life. n The weights are calculated based on the battery life correction coefficient in the preset weights. β This is the lifetime correction factor.
8. A lithium iron phosphate lithium-ion battery life assessment device, characterized in that, The device includes: The data extraction module is used to obtain the effective charging data of the lithium iron phosphate battery under test. The charging data is the charging data of the lithium iron phosphate battery under test during the charging process when the remaining power is less than 5% at the beginning of charging and greater than or equal to 98% at the end of charging. The segmentation module is used to divide the effective charging data into a first stage charging data corresponding to a first preset voltage interval within the preset voltage interval set, a second stage charging data corresponding to a second preset voltage interval within the preset voltage interval set, and a third stage charging data corresponding to a third preset voltage interval within the preset voltage interval set, according to a preset voltage interval set. The first calculation module is used to calculate the charging capacity within the first preset voltage range based on the charging start time, charging end time and battery current in the first stage charging data, and to calculate the current lifespan status of the battery based on the charging capacity, the remaining charging capacity at the start of the first stage charging data, the remaining charging capacity at the end of the first stage charging data and the capacity value of the lithium iron phosphate battery under full charge. The second calculation module is used to calculate the capacity increment data of the lithium iron phosphate battery under test based on the battery capacity change data and battery voltage change data in the second stage charging data, and to determine the offset data based on the capacity increment data and the factory data of the lithium iron phosphate battery under test. It also calculates the life correction coefficient based on the offset data, the factory data and the termination data of the lithium iron phosphate battery under test at the end of its life, and calculates the life prediction data of the lithium iron phosphate battery under test based on the current life status of the battery, the life correction coefficient and the preset weight. The verification module is used to calculate the life verification value of the lithium iron phosphate battery under test based on the third-stage charging data, and to verify the life prediction data using the life verification value. If the verification passes, the life prediction data is used as output data; if the verification fails, the preset weight is modified, and the life re-prediction data of the lithium iron phosphate battery under test is calculated based on the modified preset weight, until the life re-prediction data is verified by the life verification value, and the life re-prediction data is used as output data.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the lithium iron phosphate lithium-ion battery life assessment method as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the lithium iron phosphate lithium-ion battery life assessment method as described in any one of claims 1 to 7.